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Database Design: Logical Models: Normalization and The Relational Model University of California, Berkeley School of Information IS 257: Database Management IS 257 – Fall 2015 2015.09.17 - SLIDE 1 Lecture Outline • Review – Conceptual Model and UML – Logical Model for the Diveshop database • Normalization • Relational Advantages and Disadvantages IS 257 – Fall 2015 2015.09.17 - SLIDE 2 Lecture Outline • Normalization • Relational Advantages and Disadvantages IS 257 – Fall 2015 2015.09.17 - SLIDE 3 Normalization • Normalization theory is based on the observation that relations with certain properties are more effective in inserting, updating and deleting data than other sets of relations containing the same data • Normalization is a multi-step process beginning with an “unnormalized” relation – Hospital example from Atre, S. Data Base: Structured Techniques for Design, Performance, and Management. IS 257 – Fall 2015 2015.09.17 - SLIDE 4 Normal Forms • • • • • • First Normal Form (1NF) Second Normal Form (2NF) Third Normal Form (3NF) Boyce-Codd Normal Form (BCNF) Fourth Normal Form (4NF) Fifth Normal Form (5NF) IS 257 – Fall 2015 2015.09.17 - SLIDE 5 Normalization No transitive dependency between nonkey attributes All determinants are candidate keys - Single multivalued dependency IS 257 – Fall 2015 BoyceCodd and Higher Functional dependency of nonkey attributes on the primary key - Atomic values only Full Functional dependency of nonkey attributes on the primary key 2015.09.17 - SLIDE 6 Unnormalized Relations • First step in normalization is to convert the data into a two-dimensional table • In unnormalized relations data may repeat within a column IS 257 – Fall 2015 2015.09.17 - SLIDE 7 Unnormalized Relation Patient # Surgeon # 145 1111 311 Surg. date Jan 1, 1995; June 12, 1995 Patient Name John White Patient Addr 15 New St. New York, NY Surgeon Surgery Beth Little Michael Diamond Gallstone s removal; Kidney stones removal Postop drug Drug side effects Penicillin, none- rash none Tetracyclin e none Fever none Cephalosp orin none Demicillin none none none Eye Apr 5, 243 1234 467 1994 May 10, 1995 Mary Jones 10 Main St. Rye, NY Charles Field Cataract removal Patricia Gold Thrombos is removal Dogwood Lane 2345 189 Jan 8, 1996 Charles Brown Harrison, NY Open David Rosen Heart Surgery 55 Boston Post Road, 4876 145 Nov 5, 1995 Hal Kane 5123 145 May 10, 1995 Paul Kosher Apr 5, 1994 Dec 6845 243 IS 257 – Fall 2015 15, 1984 Ann Hood Chester, CN Blind Brook Mamaronec k, NY Hilton Road Larchmont, NY Beth Little Beth Little Cholecyst ectomy Gallstone s Removal Eye Cornea Replacem Charles ent Eye cataract Tetracyclin Field removal e Fever 2015.09.17 - SLIDE 8 First Normal Form • To move to First Normal Form a relation must contain only atomic values at each row and column. – No repeating groups – A column or set of columns is called a Candidate Key when its values can uniquely identify the row in the relation. IS 257 – Fall 2015 2015.09.17 - SLIDE 9 First Normal Form Pat ient # Surgeon # Surgery Date Pat ient Name Patient Addr Surgeon Name 15 New St. New York, 1111 145 01-Jan-95 John White 1111 311 12-Jun-95 John White 1234 243 05-Apr-94 Mary Jones 1234 467 10-May-95 Mary Jones 2345 4876 5123 189 145 145 08-Jan-96 05-Nov-95 10-May-95 NY 15 New St. New York, NY 10 Main St. Rye, NY 10 Main St. Rye, NY Dogwood Lane 6845 IS 257 – Fall 2015 243 243 05-Apr-94 15-Dec-84 Drug admin Side Effects G allstone Beth Litt le Michael Diamond s removal Kidney stones removal none none Charles Field Eye Cataract removal Tet racyclin e Fever Patricia Gold Thrombos is removal none none Penicillin rash O pen Charles Brown Harrison, NY David Rosen Heart Surgery Cephalosp orin none Hal Kane 55 Boston Post Road, Chester, CN Beth Litt le Cholecyst ectomy Demicillin none Paul Kosher Blind Brook Mamaronec k, NY Beth Litt le G allstone s Removal none none Eye Cornea Hilton Road 6845 Surgery Ann Hood Larchmont, NY Ann Hood Hilton Road Larchmont, NY Charles Field Replacem ent Tet racyclin e Fever Charles Field Eye cataract removal none none 2015.09.17 - SLIDE 10 1NF Storage Anomalies • Insertion: A new patient has not yet undergone surgery -- hence no surgeon # -- Since surgeon # is part of the key we can’t insert. • Insertion: If a surgeon is newly hired and hasn’t operated yet -- there will be no way to include that person in the database. • Update: If a patient comes in for a new procedure, and has moved, we need to change multiple address entries. • Deletion (type 1): Deleting a patient record may also delete all info about a surgeon. • Deletion (type 2): When there are functional dependencies (like side effects and drug) changing one item eliminates other information. IS 257 – Fall 2015 2015.09.17 - SLIDE 11 Second Normal Form • A relation is said to be in Second Normal Form when every nonkey attribute is fully functionally dependent on the primary key. – That is, every nonkey attribute needs the full primary key for unique identification • This is typically accomplished by projecting (think splitting) the relations into simpler relations with simpler keys IS 257 – Fall 2015 2015.09.17 - SLIDE 12 Second Normal Form Patient # 1111 1234 2345 4876 5123 6845 IS 257 – Fall 2015 Patient Name Patient Address 15 New St. New John White York, NY 10 Main St. Rye, Mary Jones NY Charles Dogwood Lane Brown Harrison, NY 55 Boston Post Hal Kane Road, Chester, Blind Brook Paul Kosher Mamaroneck, NY Hilton Road Ann Hood Larchmont, NY 2015.09.17 - SLIDE 13 Second Normal Form Surgeon # Surgeon Name 145 Beth Little 189 David Rosen 243 Charles Field 311 Michael Diamond 467 Patricia Gold IS 257 – Fall 2015 2015.09.17 - SLIDE 14 Second Normal Form Patient # Surgeon # Surgery Date 1111 1111 1234 1234 2345 4876 Drug Admin Side Effects 145 Gallstones 01-Jan-95 removal Kidney Penicillin rash 311 stones 12-Jun-95 removal none none 243 Eye Cataract 05-Apr-94 removal Tetracycline Fever 467 Thrombosis 10-May-95 removal 189 Open Heart 08-Jan-96 Surgery Cephalospori n none 145 Cholecystect 05-Nov-95 omy Demicillin none none none none none 5123 145 6845 243 6845 243 IS 257 – Fall 2015 Surgery Gallstones 10-May-95 Removal Eye cataract 15-Dec-84 removal Eye Cornea 05-Apr-94 Replacement none none Tetracycline Fever 2015.09.17 - SLIDE 15 1NF Storage Anomalies Removed • Insertion: Can now enter new patients without surgery. • Insertion: Can now enter Surgeons who haven’t operated. • Deletion (type 1): If Charles Brown dies the corresponding tuples from Patient and Surgery tables can be deleted without losing information on David Rosen. • Update: If John White comes in for third time, and has moved, we only need to change the Patient table IS 257 – Fall 2015 2015.09.17 - SLIDE 16 2NF Storage Anomalies • Insertion: Cannot enter the fact that a particular drug has a particular side effect unless it is given to a patient. • Deletion: If John White receives some other drug because of the penicillin rash, and a new drug and side effect are entered, we lose the information that penicillin can cause a rash • Update: If drug side effects change (a new formula) we have to update multiple occurrences of side effects. IS 257 – Fall 2015 2015.09.17 - SLIDE 17 Third Normal Form • A relation is said to be in Third Normal Form if there is no transitive functional dependency between nonkey attributes – When one nonkey attribute can be determined with one or more nonkey attributes there is said to be a transitive functional dependency. • The side effect column in the Surgery table is determined by the drug administered – Side effect is transitively functionally dependent on drug so Surgery is not 3NF IS 257 – Fall 2015 2015.09.17 - SLIDE 18 Third Normal Form Patient # Surgeon # Surgery Date IS 257 – Fall 2015 Surgery Drug Admin 1111 145 1111 311 01-Jan-95 Gallstones removal Kidney stones 12-Jun-95 removal 1234 243 05-Apr-94 Eye Cataract removal Tetracycline 1234 467 10-May-95 Thrombosis removal 2345 189 08-Jan-96 Open Heart Surgery Cephalosporin 4876 145 05-Nov-95 Cholecystectomy Demicillin 5123 145 10-May-95 Gallstones Removal none 6845 243 none 6845 243 15-Dec-84 Eye cataract removal Eye Cornea 05-Apr-94 Replacement Penicillin none none Tetracycline 2015.09.17 - SLIDE 19 Third Normal Form Drug Admin IS 257 – Fall 2015 Side Effects Cephalosporin none Demicillin none none none Penicillin rash Tetracycline Fever 2015.09.17 - SLIDE 20 2NF Storage Anomalies Removed • Insertion: We can now enter the fact that a particular drug has a particular side effect in the Drug relation. • Deletion: If John White recieves some other drug as a result of the rash from penicillin, but the information on penicillin and rash is maintained. • Update: The side effects for each drug appear only once. IS 257 – Fall 2015 2015.09.17 - SLIDE 21 Boyce-Codd Normal Form • Most 3NF relations are also BCNF relations. • A 3NF relation is NOT in BCNF if: – Candidate keys in the relation are composite keys (they are not single attributes) – There is more than one candidate key in the relation, and – The keys are not disjoint, that is, some attributes in the keys are common IS 257 – Fall 2015 2015.09.17 - SLIDE 22 Most 3NF Relations are also BCNF – Is this one? Patient # Patient Name Patient Address 15 New St. New 1111 John White York, NY 10 Main St. Rye, 1234 Mary Jones NY Charles Dogwood Lane 2345 Brown Harrison, NY 55 Boston Post 4876 Hal Kane Road, Chester, Blind Brook 5123 Paul Kosher Mamaroneck, NY Hilton Road 6845 Ann Hood Larchmont, NY IS 257 – Fall 2015 2015.09.17 - SLIDE 23 BCNF Relations Patient # IS 257 – Fall 2015 Patient Name Patient # 1111 John White 1111 1234 Mary Jones Charles 2345 Brown 1234 4876 Hal Kane 4876 5123 Paul Kosher 5123 6845 Ann Hood 6845 2345 Patient Address 15 New St. New York, NY 10 Main St. Rye, NY Dogwood Lane Harrison, NY 55 Boston Post Road, Chester, Blind Brook Mamaroneck, NY Hilton Road Larchmont, NY 2015.09.17 - SLIDE 24 Fourth Normal Form • Any relation is in Fourth Normal Form if it is BCNF and any multivalued dependencies are trivial • Eliminate non-trivial multivalued dependencies by projecting into simpler tables IS 257 – Fall 2015 2015.09.17 - SLIDE 25 Fourth Normal Form Example Restaurant Pizza Variety Delivery Area Zoppo’s Pizza Thick Crust Berkeley Zoppo’s Pizza Thick Crust Albany Zoppo’s Pizza Thick Crust Oakland Zoppo’s Pizza Stuffed Crust Berkeley Zoppo’s Pizza Stuffed Crust Albany Zoppo’s Pizza Stuffed Crust Oakland Domino’s Thin Crust Oakland Domino’s Stuffed Crust Oakland Xtreme Pizza Thick Crust Berkeley Xtreme Pizza Thick Crust Albany Xtreme Pizza Thin Crust Berkeley Xtreme Pizza Thin Crust Albany … IS 257 – Fall 2015 2015.09.17 - SLIDE 26 Fourth Normal Form Example • Each row indicates that a particular restaurant can delivery a particular kind of pizza to a particular city. • There are NO non-key attributes because the only key is (Restaurant, Pizza Variety, Delivery Area). • But, if we assume that the Pizza Varieties for a given Restaurant are the same regardless of the delivery area, then it is NOT in fourth normal form. IS 257 – Fall 2015 2015.09.17 - SLIDE 27 Fourth Normal Form Example • The table features two non-trivial multivalued dependencies on the Restaurant attribute (which is not a superkey) • These are: – Restaurant ->> Pizza Variety – Restaurant ->> Delivery Area • This leads to redundancy in the table (e.g., we are told three times that Zoppo’s has Thick Crust) IS 257 – Fall 2015 2015.09.17 - SLIDE 28 Fourth Normal Form Example • If Zoppo’s Pizza starts producing Cheese Crust pizzas then we will need to add multiple rows, one for each of Zoppo's delivery areas – And there’s nothing to stop us from doing this incorrectly by not including each delivery area • To eliminate these anomalies, the facts about varieties offered can be put in a different table from the facts about delivery areas • This gives us two tables that are both in 4NF IS 257 – Fall 2015 2015.09.17 - SLIDE 29 Fourth Normal Form Example Restaurant Pizza Variety Restaurant Delivery Area Zoppo’s Pizza Thick Crust Zoppo’s Pizza Berkeley Zoppo’s Pizza Stuffed Crust Zoppo’s Pizza Albany Domino’s Thin Crust Zoppo’s Pizza Oakland Domino’s Stuffed Crust Domino’s Oakland Xtreme Pizza Thick Crust Xtreme Pizza Berkeley Xtreme Pizza Thin Crust Xtreme Pizza Albany IS 257 – Fall 2015 2015.09.17 - SLIDE 30 Fourth Normal Form Example • But, suppose that the pizza varieties offered by a restaurant sometimes did legitimately vary from one delivery area to another, the original three-column table would satisfy 4NF IS 257 – Fall 2015 2015.09.17 - SLIDE 31 Fifth Normal Form • A relation is in 5NF if every join dependency in the relation is implied by the keys of the relation • And if it cannot have a lossless decomposition into any number of smaller tables • Implies that relations that have been decomposed in previous NF can be recombined via natural joins to recreate the original NF relations IS 257 – Fall 2015 2015.09.17 - SLIDE 32 Normalization • Normalization is performed to reduce or eliminate Insertion, Deletion or Update anomalies. • However, a completely normalized database may not be the most efficient or effective implementation. • “Denormalization” is sometimes used to improve efficiency. IS 257 – Fall 2015 2015.09.17 - SLIDE 33 Normalizing to death • Normalization splits database information across multiple tables. • To retrieve complete information from a normalized database, the JOIN operation must be used. • JOIN tends to be expensive in terms of processing time, and very large joins are very expensive. IS 257 – Fall 2015 2015.09.17 - SLIDE 34 Denormalization • Usually driven by the need to improve query speed • Query speed is improved at the expense of more complex or problematic DML (Data manipulation language) for updates, deletions and insertions. IS 257 – Fall 2015 2015.09.17 - SLIDE 35 Downward Denormalization Customer ID Address Name Telephone Before: Order Order No Date Taken Date Dispatched Date Invoiced Cust ID IS 257 – Fall 2015 After: Customer ID Address Name Telephone Order Order No Date Taken Date Dispatched Date Invoiced Cust ID Cust Name 2015.09.17 - SLIDE 36 Upward Denormalization Order Order No Date Taken Date Dispatched Date Invoiced Cust ID Cust Name Order Item Order No Item No Item Price Num Ordered IS 257 – Fall 2015 Order Order No Date Taken Date Dispatched Date Invoiced Cust ID Cust Name Order Price Order Item Order No Item No Item Price Num Ordered 2015.09.17 - SLIDE 37 Using RDBMS to help normalize • Example database: Cookie • Database of books, libraries, publisher and holding information for a shared (union) catalog IS 257 – Fall 2015 2015.09.17 - SLIDE 38 Cookie relationships IS 257 – Fall 2015 2015.09.17 - SLIDE 39 Cookie BIBFILE relation ACCNO A003 T082 C024 B006 B007 B005 B008 B010 B009 B012 B011 B014 B013 B016 B017 F047 B116 S102 B118 B018 C031 C032 C034 AUTHOR TITLE LOC PUBID DATE AMERICAN LIBRARY ASSOCIATION ALA BULLETIN CHICAGO 04 ANDERSON, THEODORE THE TEACHING OF MODERN PARIS LANGUAGES53 1955 AXT, RICHARD G. COLLEGE SELF STUDYBOULDER, : LECTURES CO.ON INSTITU 51 1960 BALDERSTON, FREDERICKMANAGING E. TODAYS UNIVERSITY SAN FRANCISCO 27 1975 BARZUN, JACQUES TEACHER IN AMERICA GARDEN CITY 18 1954 BARZUN, JACQUES THE AMERICAN UNIVERSITY NEW YORK : HOW IT RUNS, 24 W 1970 BARZUN, JACQUES THE HOUSE OF INTELLECT NEW YORK 24 1961 BELL, DANIEL THE COMING OF POST-INDUSTRIAL NEW YORK SOCIETY 09 : 1976 BENSON, CHARLES S. IMPLEMENTING THE LEARNING SAN FRANCISCO SOCIETY 27 1974 BERG, IVAR EDUCATION AND JOBSBOSTON : THE GREAT TRAINING 10 1971 BERSI, ROBERT M. RESTRUCTURING THE BACCALAUREATE WASHINGTON, D.C.03 1973 BEVERIDGE, WILLIAM I. THE ART OF SCIENTIFIC NEW INVESTIGATION YORK 58 1957 BIRD, CAROLINE THE CASE AGAINST COLLEGE NEW YORK 08 1975 BISSELL, CLAUDE T. THE STRENGTH OF THE TORONTO UNIVERSITY 57 1968 BLAIR, GLENN MYERS EDUCATIONAL PSYCHOLOGY NEW YORK 30 1962 BLAKE, ELIAS, JR. THE FUTURE OF THE BLACK CAMBRIDGE, COLLEGES MA. 02 1971 BOLAND, R.J. CRITICAL ISSUES IN INFORMATION CHICHESTER, SYSTEMS ENG.63 R 1987 BROWN, SANBORN C., ED. SCIENTIFIC MANPOWER CAMBRIDGE, MASS. 29 1971 BUCKLAND, MICHAEL K. LIBRARY SERVICES IN ELMSFORD, THEORY ANDNY CONTEXT 70 1983 BUDIG, GENE A. ACADEMIC QUICKSANDLINCOLN, : SOME NEBRASKA TRENDS AND 37 ISS 1973 CALIFORNIA. DEPT. OF JUSTICE LAW IN THE SCHOOL MONTCLAIR, N.J. 35 1974 CAMPBELL, MARGARET A.WHY WOULD A GIRL GO OLD INTO WESTBURY, MEDICINE? N.Y. 48 1973 CARNEGIE COMMISSION ON A DIGEST HIGHER OF REPORTS NEW OF YORK THE CARNEGIE 30 COMM 1974 IS 257 – Fall 2015 PRICE $3.00 $10.95 $7.00 $6.00 $7.00 $5.00 $8.00 $10.00 $9.00 $12.00 $11.00 $14.00 $13.00 $14.00 $11.00 $14.25 $30.95 $4.00 $12.00 $13.00 $0.50 $1.50 $3.50 PAGINATION ILL 63 V. ILL. 294 P. X, 300 P. GRAPHS XVI, 307 P. 280 P. XII, 319 P. VIII, 271 P. XXVII, 507 P. XVII, 147 P. XX, 200 P. IV, 160P. XIV, 239 P. XII, 308 P. VII, 251 P. 678 P. VIII, PP. 539 XV, 394 P. ILL. X, 180 P. XII, 201 P. ILL. 74 P. IV, 87 P. V, 114 P. 399 P. HEIGHT 26 22 28 24 18 20 21 21 24 21 23 18 18 21 24 23 24 26 23 23 21 24 24 2015.09.17 - SLIDE 40 How to Normalize? • Currently no way to have multiple authors for a given book, and there is duplicate data spread over the BIBFILE table • Can we use the DBMS to help us normalize? • It is possible (but takes a bit more SQL knowledge than has been hinted at so far) – We will return to this problem later – But CONCEPTUALLY… IS 257 – Fall 2015 2015.09.17 - SLIDE 41 Using RDBMS to Normalize Create a new table for Authors that includes author name and an automatically incrementing id number (for primary key) Populate the table using the unique author names (which get assigned id numbers) by extracting them from the BIBFILE… CREATE TABLE AUTHORS (AU_ID INT AUTO_INCREMENT PRIMARY KEY) ; Create a new table containing a author_id and an ACCNO Populate the new table by matching the Authors and BIBFILE names… AS SELECT DISTINCT (Author) from BIBFILE CREATE TABLE AU_BIB (AU_ID INT, ACCNO INT) AS SELECT AUTHORS.AU_ID, BIBFILE.ACCNO FROM AUTHORS, BIBFILE WHERE AUTHORS.Author = BIBFILE.Author; Drop the Author name column from BIBFILE ALTER TABLE BIBFILE DROP COLUMN Author IS 257 – Fall 2015 2015.09.17 - SLIDE 42 Lecture Outline • Review – Logical Model for the Diveshop database • Normalization • Relational Advantages and Disadvantages IS 257 – Fall 2015 2015.09.17 - SLIDE 43 Advantages of RDBMS • Relational Database Management Systems (RDBMS) • Possible to design complex data storage and retrieval systems with ease (and without conventional programming). • Support for ACID transactions – Atomic – Consistent – Independent – Durable IS 257 – Fall 2015 2015.09.17 - SLIDE 44 Advantages of RDBMS • Support for very large databases • Automatic optimization of searching (when possible) • RDBMS have a simple view of the database that conforms to much of the data used in business • Standard query language (SQL) IS 257 – Fall 2015 2015.09.17 - SLIDE 45 Disadvantages of RDBMS • Until recently, no real support for complex objects such as documents, video, images, spatial or time-series data. (ORDBMS add -- or make available support for these) • Often poor support for storage of complex objects from OOP languages (Disassembling the car to park it in the garage) • Usually no efficient and effective integrated support for things like text searching within fields (MySQL now does have simple keyword searching with index support, but no ranking) IS 257 – Fall 2015 2015.09.17 - SLIDE 46 Effectiveness and Efficiency Issues for DBMS • Our primary focus has been, and will continue to be, on the relational model • Any column in a relational database can be searched for values • To improve efficiency indexes using storage structures such as BTrees and Hashing are used • But many useful functions are not indexable and require complete scans of the the database IS 257 – Fall 2015 2015.09.17 - SLIDE 47 Example: Text Fields • In conventional RDBMS, when a text field is indexed, only exact matching of the text field contents (or Greater-than and Lessthan). – Can search for individual words using pattern matching, but a full scan is required. • Text searching is still done best (and fastest) by specialized text search programs (Search Engines) that we will look at more later IS 257 – Fall 2015 2015.09.17 - SLIDE 48 Next Week • (Re)Introduction to SQL • More on Logical Design/Normalization • Physical Design IS 257 – Fall 2015 2015.09.17 - SLIDE 49